API - Application Point interface¶

ek baar square brcket mein likho link aur dusre baar round bracket mein likho link fir sirf link display hogi brackets nhi....¶

Create an account on - https://rapidapi.com/auth/sign-up

API 1- https://rapidapi.com/alphavantage/api/alpha-vantage

In [1]:
import requests

url = "https://alpha-vantage.p.rapidapi.com/query"

querystring = {"function":"TIME_SERIES_DAILY","symbol":"AAPL","outputsize":"compact","datatype":"json"}

headers = {
    "X-RapidAPI-Key": "4671befe8emsh7013c7cb33388c1p12bea1jsna736eefbd6fc",
    "X-RapidAPI-Host": "alpha-vantage.p.rapidapi.com"
}

response = requests.get(url, headers=headers, params=querystring)

print(response.json())

{'Meta Data': {'1. Information': 'Daily Prices (open, high, low, close) and Volumes', '2. Symbol': 'AAPL', '3. Last Refreshed': '2023-12-22', '4. Output Size': 'Compact', '5. Time Zone': 'US/Eastern'}, 'Time Series (Daily)': {'2023-12-22': {'1. open': '195.1800', '2. high': '195.4100', '3. low': '192.9700', '4. close': '193.6000', '5. volume': '37149570'}, '2023-12-21': {'1. open': '196.1000', '2. high': '197.0800', '3. low': '193.5000', '4. close': '194.6800', '5. volume': '46482549'}, '2023-12-20': {'1. open': '196.9000', '2. high': '197.6800', '3. low': '194.8300', '4. close': '194.8300', '5. volume': '52242815'}, '2023-12-19': {'1. open': '196.1600', '2. high': '196.9500', '3. low': '195.8900', '4. close': '196.9400', '5. volume': '40233138'}, '2023-12-18': {'1. open': '196.0900', '2. high': '196.6300', '3. low': '194.3900', '4. close': '195.8900', '5. volume': '55751861'}, '2023-12-15': {'1. open': '197.5300', '2. high': '198.3999', '3. low': '197.0000', '4. close': '197.5700', '5. volume': '128538401'}, '2023-12-14': {'1. open': '198.0200', '2. high': '199.6200', '3. low': '196.1600', '4. close': '198.1100', '5. volume': '66831572'}, '2023-12-13': {'1. open': '195.0900', '2. high': '198.0000', '3. low': '194.8500', '4. close': '197.9600', '5. volume': '70404183'}, '2023-12-12': {'1. open': '193.0800', '2. high': '194.7200', '3. low': '191.7210', '4. close': '194.7100', '5. volume': '52696900'}, '2023-12-11': {'1. open': '193.1100', '2. high': '193.4900', '3. low': '191.4200', '4. close': '193.1800', '5. volume': '60943699'}, '2023-12-08': {'1. open': '194.2000', '2. high': '195.9900', '3. low': '193.6700', '4. close': '195.7100', '5. volume': '53406358'}, '2023-12-07': {'1. open': '193.6300', '2. high': '195.0000', '3. low': '193.5900', '4. close': '194.2700', '5. volume': '47477655'}, '2023-12-06': {'1. open': '194.4500', '2. high': '194.7600', '3. low': '192.1100', '4. close': '192.3200', '5. volume': '40895115'}, '2023-12-05': {'1. open': '190.2100', '2. high': '194.4000', '3. low': '190.1800', '4. close': '193.4200', '5. volume': '66628398'}, '2023-12-04': {'1. open': '189.9800', '2. high': '190.0500', '3. low': '187.4511', '4. close': '189.4300', '5. volume': '43389519'}, '2023-12-01': {'1. open': '190.3300', '2. high': '191.5600', '3. low': '189.2300', '4. close': '191.2400', '5. volume': '45704823'}, '2023-11-30': {'1. open': '189.8400', '2. high': '190.3200', '3. low': '188.1900', '4. close': '189.9500', '5. volume': '48794366'}, '2023-11-29': {'1. open': '190.9000', '2. high': '192.0900', '3. low': '188.9700', '4. close': '189.3700', '5. volume': '43014224'}, '2023-11-28': {'1. open': '189.7800', '2. high': '191.0800', '3. low': '189.4000', '4. close': '190.4000', '5. volume': '38415419'}, '2023-11-27': {'1. open': '189.9200', '2. high': '190.6700', '3. low': '188.9000', '4. close': '189.7900', '5. volume': '40552609'}, '2023-11-24': {'1. open': '190.8700', '2. high': '190.9000', '3. low': '189.2500', '4. close': '189.9700', '5. volume': '24048344'}, '2023-11-22': {'1. open': '191.4900', '2. high': '192.9300', '3. low': '190.8250', '4. close': '191.3100', '5. volume': '39630011'}, '2023-11-21': {'1. open': '191.4100', '2. high': '191.5200', '3. low': '189.7400', '4. close': '190.6400', '5. volume': '38134485'}, '2023-11-20': {'1. open': '189.8900', '2. high': '191.9050', '3. low': '189.8800', '4. close': '191.4500', '5. volume': '46538614'}, '2023-11-17': {'1. open': '190.2500', '2. high': '190.3800', '3. low': '188.5700', '4. close': '189.6900', '5. volume': '50941404'}, '2023-11-16': {'1. open': '189.5700', '2. high': '190.9600', '3. low': '188.6500', '4. close': '189.7100', '5. volume': '54412915'}, '2023-11-15': {'1. open': '187.8450', '2. high': '189.5000', '3. low': '187.7800', '4. close': '188.0100', '5. volume': '53790499'}, '2023-11-14': {'1. open': '187.7000', '2. high': '188.1100', '3. low': '186.3000', '4. close': '187.4400', '5. volume': '60108378'}, '2023-11-13': {'1. open': '185.8200', '2. high': '186.0300', '3. low': '184.2100', '4. close': '184.8000', '5. volume': '43627519'}, '2023-11-10': {'1. open': '183.9700', '2. high': '186.5650', '3. low': '183.5300', '4. close': '186.4000', '5. volume': '66177922'}, '2023-11-09': {'1. open': '182.9600', '2. high': '184.1200', '3. low': '181.8100', '4. close': '182.4100', '5. volume': '53763540'}, '2023-11-08': {'1. open': '182.3500', '2. high': '183.4500', '3. low': '181.5900', '4. close': '182.8900', '5. volume': '49340282'}, '2023-11-07': {'1. open': '179.1800', '2. high': '182.4400', '3. low': '178.9700', '4. close': '181.8200', '5. volume': '70529966'}, '2023-11-06': {'1. open': '176.3800', '2. high': '179.4300', '3. low': '176.2100', '4. close': '179.2300', '5. volume': '63841310'}, '2023-11-03': {'1. open': '174.2400', '2. high': '176.8200', '3. low': '173.3500', '4. close': '176.6500', '5. volume': '79829246'}, '2023-11-02': {'1. open': '175.5200', '2. high': '177.7800', '3. low': '175.4600', '4. close': '177.5700', '5. volume': '77334752'}, '2023-11-01': {'1. open': '171.0000', '2. high': '174.2300', '3. low': '170.1200', '4. close': '173.9700', '5. volume': '56934906'}, '2023-10-31': {'1. open': '169.3500', '2. high': '170.9000', '3. low': '167.9000', '4. close': '170.7700', '5. volume': '44846017'}, '2023-10-30': {'1. open': '169.0200', '2. high': '171.1700', '3. low': '168.8700', '4. close': '170.2900', '5. volume': '51130955'}, '2023-10-27': {'1. open': '166.9100', '2. high': '168.9600', '3. low': '166.8300', '4. close': '168.2200', '5. volume': '58499129'}, '2023-10-26': {'1. open': '170.3700', '2. high': '171.3775', '3. low': '165.6700', '4. close': '166.8900', '5. volume': '70625258'}, '2023-10-25': {'1. open': '171.8800', '2. high': '173.0600', '3. low': '170.6500', '4. close': '171.1000', '5. volume': '57156962'}, '2023-10-24': {'1. open': '173.0500', '2. high': '173.6700', '3. low': '171.4500', '4. close': '173.4400', '5. volume': '43816644'}, '2023-10-23': {'1. open': '170.9100', '2. high': '174.0100', '3. low': '169.9300', '4. close': '173.0000', '5. volume': '55980109'}, '2023-10-20': {'1. open': '175.3100', '2. high': '175.4200', '3. low': '172.6400', '4. close': '172.8800', '5. volume': '64244028'}, '2023-10-19': {'1. open': '176.0400', '2. high': '177.8400', '3. low': '175.1900', '4. close': '175.4600', '5. volume': '59302863'}, '2023-10-18': {'1. open': '175.5800', '2. high': '177.5750', '3. low': '175.1100', '4. close': '175.8400', '5. volume': '54764375'}, '2023-10-17': {'1. open': '176.6450', '2. high': '178.4200', '3. low': '174.8000', '4. close': '177.1500', '5. volume': '57549350'}, '2023-10-16': {'1. open': '176.7500', '2. high': '179.0750', '3. low': '176.5100', '4. close': '178.7200', '5. volume': '52516984'}, '2023-10-13': {'1. open': '181.4200', '2. high': '181.9300', '3. low': '178.1400', '4. close': '178.8500', '5. volume': '51456082'}, '2023-10-12': {'1. open': '180.0700', '2. high': '182.3400', '3. low': '179.0400', '4. close': '180.7100', '5. volume': '56743119'}, '2023-10-11': {'1. open': '178.2000', '2. high': '179.8500', '3. low': '177.6000', '4. close': '179.8000', '5. volume': '47551098'}, '2023-10-10': {'1. open': '178.1000', '2. high': '179.7200', '3. low': '177.9500', '4. close': '178.3900', '5. volume': '43698019'}, '2023-10-09': {'1. open': '176.8100', '2. high': '179.0500', '3. low': '175.8000', '4. close': '178.9900', '5. volume': '42390772'}, '2023-10-06': {'1. open': '173.8000', '2. high': '177.9900', '3. low': '173.1800', '4. close': '177.4900', '5. volume': '57266675'}, '2023-10-05': {'1. open': '173.7900', '2. high': '175.4500', '3. low': '172.6800', '4. close': '174.9100', '5. volume': '48527918'}, '2023-10-04': {'1. open': '171.0900', '2. high': '174.2100', '3. low': '170.9700', '4. close': '173.6600', '5. volume': '53020286'}, '2023-10-03': {'1. open': '172.2550', '2. high': '173.6300', '3. low': '170.8200', '4. close': '172.4000', '5. volume': '49594613'}, '2023-10-02': {'1. open': '171.2200', '2. high': '174.3000', '3. low': '170.9300', '4. close': '173.7500', '5. volume': '52164535'}, '2023-09-29': {'1. open': '172.0200', '2. high': '173.0700', '3. low': '170.3410', '4. close': '171.2100', '5. volume': '51861083'}, '2023-09-28': {'1. open': '169.3400', '2. high': '172.0300', '3. low': '167.6200', '4. close': '170.6900', '5. volume': '56294419'}, '2023-09-27': {'1. open': '172.6200', '2. high': '173.0400', '3. low': '169.0500', '4. close': '170.4300', '5. volume': '66921808'}, '2023-09-26': {'1. open': '174.8200', '2. high': '175.2000', '3. low': '171.6600', '4. close': '171.9600', '5. volume': '64588945'}, '2023-09-25': {'1. open': '174.2000', '2. high': '176.9700', '3. low': '174.1500', '4. close': '176.0800', '5. volume': '46172740'}, '2023-09-22': {'1. open': '174.6700', '2. high': '177.0790', '3. low': '174.0500', '4. close': '174.7900', '5. volume': '56725385'}, '2023-09-21': {'1. open': '174.5500', '2. high': '176.3000', '3. low': '173.8600', '4. close': '173.9300', '5. volume': '63149116'}, '2023-09-20': {'1. open': '179.2600', '2. high': '179.6950', '3. low': '175.4000', '4. close': '175.4900', '5. volume': '58436181'}, '2023-09-19': {'1. open': '177.5200', '2. high': '179.6300', '3. low': '177.1300', '4. close': '179.0700', '5. volume': '51826941'}, '2023-09-18': {'1. open': '176.4800', '2. high': '179.3800', '3. low': '176.1700', '4. close': '177.9700', '5. volume': '67257573'}, '2023-09-15': {'1. open': '176.4800', '2. high': '176.4950', '3. low': '173.8200', '4. close': '175.0100', '5. volume': '109259461'}, '2023-09-14': {'1. open': '174.0000', '2. high': '176.1000', '3. low': '173.5800', '4. close': '175.7400', '5. volume': '60895757'}, '2023-09-13': {'1. open': '176.5100', '2. high': '177.3000', '3. low': '173.9800', '4. close': '174.2100', '5. volume': '84267928'}, '2023-09-12': {'1. open': '179.4900', '2. high': '180.1300', '3. low': '174.8200', '4. close': '176.3000', '5. volume': '90370192'}, '2023-09-11': {'1. open': '180.0700', '2. high': '180.3000', '3. low': '177.3400', '4. close': '179.3600', '5. volume': '58953052'}, '2023-09-08': {'1. open': '178.3500', '2. high': '180.2390', '3. low': '177.7900', '4. close': '178.1800', '5. volume': '65602066'}, '2023-09-07': {'1. open': '175.1800', '2. high': '178.2100', '3. low': '173.5400', '4. close': '177.5600', '5. volume': '112488803'}, '2023-09-06': {'1. open': '188.4000', '2. high': '188.8500', '3. low': '181.4700', '4. close': '182.9100', '5. volume': '81755816'}, '2023-09-05': {'1. open': '188.2800', '2. high': '189.9800', '3. low': '187.6100', '4. close': '189.7000', '5. volume': '45280027'}, '2023-09-01': {'1. open': '189.4850', '2. high': '189.9200', '3. low': '188.2800', '4. close': '189.4600', '5. volume': '45766503'}, '2023-08-31': {'1. open': '187.8400', '2. high': '189.1200', '3. low': '187.4800', '4. close': '187.8700', '5. volume': '60794467'}, '2023-08-30': {'1. open': '184.9400', '2. high': '187.8500', '3. low': '184.7400', '4. close': '187.6500', '5. volume': '60813888'}, '2023-08-29': {'1. open': '179.6950', '2. high': '184.9000', '3. low': '179.5000', '4. close': '184.1200', '5. volume': '53003948'}, '2023-08-28': {'1. open': '180.0900', '2. high': '180.5900', '3. low': '178.5450', '4. close': '180.1900', '5. volume': '43820697'}, '2023-08-25': {'1. open': '177.3800', '2. high': '179.1500', '3. low': '175.8200', '4. close': '178.6100', '5. volume': '51449594'}, '2023-08-24': {'1. open': '180.6740', '2. high': '181.1040', '3. low': '176.0100', '4. close': '176.3800', '5. volume': '54945798'}, '2023-08-23': {'1. open': '178.5200', '2. high': '181.5500', '3. low': '178.3250', '4. close': '181.1200', '5. volume': '52722752'}, '2023-08-22': {'1. open': '177.0600', '2. high': '177.6800', '3. low': '176.2500', '4. close': '177.2300', '5. volume': '42084245'}, '2023-08-21': {'1. open': '175.0700', '2. high': '176.1300', '3. low': '173.7350', '4. close': '175.8400', '5. volume': '46311879'}, '2023-08-18': {'1. open': '172.3000', '2. high': '175.1000', '3. low': '171.9600', '4. close': '174.4900', '5. volume': '61172150'}, '2023-08-17': {'1. open': '177.1400', '2. high': '177.5054', '3. low': '173.4800', '4. close': '174.0000', '5. volume': '66062882'}, '2023-08-16': {'1. open': '177.1300', '2. high': '178.5400', '3. low': '176.5000', '4. close': '176.5700', '5. volume': '46964857'}, '2023-08-15': {'1. open': '178.8800', '2. high': '179.4800', '3. low': '177.0500', '4. close': '177.4500', '5. volume': '43622593'}, '2023-08-14': {'1. open': '177.9700', '2. high': '179.6900', '3. low': '177.3050', '4. close': '179.4600', '5. volume': '43675627'}, '2023-08-11': {'1. open': '177.3200', '2. high': '178.6200', '3. low': '176.5500', '4. close': '177.7900', '5. volume': '52036672'}, '2023-08-10': {'1. open': '179.4800', '2. high': '180.7500', '3. low': '177.6000', '4. close': '177.9700', '5. volume': '54686851'}, '2023-08-09': {'1. open': '180.8700', '2. high': '180.9300', '3. low': '177.0100', '4. close': '178.1900', '5. volume': '60378492'}, '2023-08-08': {'1. open': '179.6900', '2. high': '180.2700', '3. low': '177.5800', '4. close': '179.8000', '5. volume': '67823003'}, '2023-08-07': {'1. open': '182.1300', '2. high': '183.1300', '3. low': '177.3500', '4. close': '178.8500', '5. volume': '97576069'}, '2023-08-04': {'1. open': '185.5200', '2. high': '187.3800', '3. low': '181.9200', '4. close': '181.9900', '5. volume': '115956841'}, '2023-08-03': {'1. open': '191.5700', '2. high': '192.3700', '3. low': '190.6900', '4. close': '191.1700', '5. volume': '62243282'}}}
In [2]:
data = response.json()
In [3]:
data
Out[3]:
{'Meta Data': {'1. Information': 'Daily Prices (open, high, low, close) and Volumes',
  '2. Symbol': 'AAPL',
  '3. Last Refreshed': '2023-12-22',
  '4. Output Size': 'Compact',
  '5. Time Zone': 'US/Eastern'},
 'Time Series (Daily)': {'2023-12-22': {'1. open': '195.1800',
   '2. high': '195.4100',
   '3. low': '192.9700',
   '4. close': '193.6000',
   '5. volume': '37149570'},
  '2023-12-21': {'1. open': '196.1000',
   '2. high': '197.0800',
   '3. low': '193.5000',
   '4. close': '194.6800',
   '5. volume': '46482549'},
  '2023-12-20': {'1. open': '196.9000',
   '2. high': '197.6800',
   '3. low': '194.8300',
   '4. close': '194.8300',
   '5. volume': '52242815'},
  '2023-12-19': {'1. open': '196.1600',
   '2. high': '196.9500',
   '3. low': '195.8900',
   '4. close': '196.9400',
   '5. volume': '40233138'},
  '2023-12-18': {'1. open': '196.0900',
   '2. high': '196.6300',
   '3. low': '194.3900',
   '4. close': '195.8900',
   '5. volume': '55751861'},
  '2023-12-15': {'1. open': '197.5300',
   '2. high': '198.3999',
   '3. low': '197.0000',
   '4. close': '197.5700',
   '5. volume': '128538401'},
  '2023-12-14': {'1. open': '198.0200',
   '2. high': '199.6200',
   '3. low': '196.1600',
   '4. close': '198.1100',
   '5. volume': '66831572'},
  '2023-12-13': {'1. open': '195.0900',
   '2. high': '198.0000',
   '3. low': '194.8500',
   '4. close': '197.9600',
   '5. volume': '70404183'},
  '2023-12-12': {'1. open': '193.0800',
   '2. high': '194.7200',
   '3. low': '191.7210',
   '4. close': '194.7100',
   '5. volume': '52696900'},
  '2023-12-11': {'1. open': '193.1100',
   '2. high': '193.4900',
   '3. low': '191.4200',
   '4. close': '193.1800',
   '5. volume': '60943699'},
  '2023-12-08': {'1. open': '194.2000',
   '2. high': '195.9900',
   '3. low': '193.6700',
   '4. close': '195.7100',
   '5. volume': '53406358'},
  '2023-12-07': {'1. open': '193.6300',
   '2. high': '195.0000',
   '3. low': '193.5900',
   '4. close': '194.2700',
   '5. volume': '47477655'},
  '2023-12-06': {'1. open': '194.4500',
   '2. high': '194.7600',
   '3. low': '192.1100',
   '4. close': '192.3200',
   '5. volume': '40895115'},
  '2023-12-05': {'1. open': '190.2100',
   '2. high': '194.4000',
   '3. low': '190.1800',
   '4. close': '193.4200',
   '5. volume': '66628398'},
  '2023-12-04': {'1. open': '189.9800',
   '2. high': '190.0500',
   '3. low': '187.4511',
   '4. close': '189.4300',
   '5. volume': '43389519'},
  '2023-12-01': {'1. open': '190.3300',
   '2. high': '191.5600',
   '3. low': '189.2300',
   '4. close': '191.2400',
   '5. volume': '45704823'},
  '2023-11-30': {'1. open': '189.8400',
   '2. high': '190.3200',
   '3. low': '188.1900',
   '4. close': '189.9500',
   '5. volume': '48794366'},
  '2023-11-29': {'1. open': '190.9000',
   '2. high': '192.0900',
   '3. low': '188.9700',
   '4. close': '189.3700',
   '5. volume': '43014224'},
  '2023-11-28': {'1. open': '189.7800',
   '2. high': '191.0800',
   '3. low': '189.4000',
   '4. close': '190.4000',
   '5. volume': '38415419'},
  '2023-11-27': {'1. open': '189.9200',
   '2. high': '190.6700',
   '3. low': '188.9000',
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In [4]:
data.keys()
Out[4]:
dict_keys(['Meta Data', 'Time Series (Daily)'])
In [5]:
data.items()
Out[5]:
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close': '174.0000', '5. volume': '66062882'}, '2023-08-16': {'1. open': '177.1300', '2. high': '178.5400', '3. low': '176.5000', '4. close': '176.5700', '5. volume': '46964857'}, '2023-08-15': {'1. open': '178.8800', '2. high': '179.4800', '3. low': '177.0500', '4. close': '177.4500', '5. volume': '43622593'}, '2023-08-14': {'1. open': '177.9700', '2. high': '179.6900', '3. low': '177.3050', '4. close': '179.4600', '5. volume': '43675627'}, '2023-08-11': {'1. open': '177.3200', '2. high': '178.6200', '3. low': '176.5500', '4. close': '177.7900', '5. volume': '52036672'}, '2023-08-10': {'1. open': '179.4800', '2. high': '180.7500', '3. low': '177.6000', '4. close': '177.9700', '5. volume': '54686851'}, '2023-08-09': {'1. open': '180.8700', '2. high': '180.9300', '3. low': '177.0100', '4. close': '178.1900', '5. volume': '60378492'}, '2023-08-08': {'1. open': '179.6900', '2. high': '180.2700', '3. low': '177.5800', '4. close': '179.8000', '5. volume': '67823003'}, '2023-08-07': {'1. 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In [6]:
data.keys()
Out[6]:
dict_keys(['Meta Data', 'Time Series (Daily)'])
In [7]:
data['Meta Data']
Out[7]:
{'1. Information': 'Daily Prices (open, high, low, close) and Volumes',
 '2. Symbol': 'AAPL',
 '3. Last Refreshed': '2023-12-22',
 '4. Output Size': 'Compact',
 '5. Time Zone': 'US/Eastern'}
In [8]:
data['Time Series (Daily)']
Out[8]:
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  '2. high': '195.4100',
  '3. low': '192.9700',
  '4. close': '193.6000',
  '5. volume': '37149570'},
 '2023-12-21': {'1. open': '196.1000',
  '2. high': '197.0800',
  '3. low': '193.5000',
  '4. close': '194.6800',
  '5. volume': '46482549'},
 '2023-12-20': {'1. open': '196.9000',
  '2. high': '197.6800',
  '3. low': '194.8300',
  '4. close': '194.8300',
  '5. volume': '52242815'},
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  '2. high': '196.9500',
  '3. low': '195.8900',
  '4. close': '196.9400',
  '5. volume': '40233138'},
 '2023-12-18': {'1. open': '196.0900',
  '2. high': '196.6300',
  '3. low': '194.3900',
  '4. close': '195.8900',
  '5. volume': '55751861'},
 '2023-12-15': {'1. open': '197.5300',
  '2. high': '198.3999',
  '3. low': '197.0000',
  '4. close': '197.5700',
  '5. volume': '128538401'},
 '2023-12-14': {'1. open': '198.0200',
  '2. high': '199.6200',
  '3. low': '196.1600',
  '4. close': '198.1100',
  '5. volume': '66831572'},
 '2023-12-13': {'1. open': '195.0900',
  '2. high': '198.0000',
  '3. low': '194.8500',
  '4. close': '197.9600',
  '5. volume': '70404183'},
 '2023-12-12': {'1. open': '193.0800',
  '2. high': '194.7200',
  '3. low': '191.7210',
  '4. close': '194.7100',
  '5. volume': '52696900'},
 '2023-12-11': {'1. open': '193.1100',
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  '4. close': '193.1800',
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 '2023-12-08': {'1. open': '194.2000',
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  '4. close': '195.7100',
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 '2023-12-07': {'1. open': '193.6300',
  '2. high': '195.0000',
  '3. low': '193.5900',
  '4. close': '194.2700',
  '5. volume': '47477655'},
 '2023-12-06': {'1. open': '194.4500',
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  '3. low': '192.1100',
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 '2023-12-05': {'1. open': '190.2100',
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 '2023-12-04': {'1. open': '189.9800',
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 '2023-12-01': {'1. open': '190.3300',
  '2. high': '191.5600',
  '3. low': '189.2300',
  '4. close': '191.2400',
  '5. volume': '45704823'},
 '2023-11-30': {'1. open': '189.8400',
  '2. high': '190.3200',
  '3. low': '188.1900',
  '4. close': '189.9500',
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 '2023-11-29': {'1. open': '190.9000',
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  '4. close': '189.3700',
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 '2023-11-28': {'1. open': '189.7800',
  '2. high': '191.0800',
  '3. low': '189.4000',
  '4. close': '190.4000',
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 '2023-11-27': {'1. open': '189.9200',
  '2. high': '190.6700',
  '3. low': '188.9000',
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 '2023-11-24': {'1. open': '190.8700',
  '2. high': '190.9000',
  '3. low': '189.2500',
  '4. close': '189.9700',
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 '2023-11-22': {'1. open': '191.4900',
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 '2023-11-21': {'1. open': '191.4100',
  '2. high': '191.5200',
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 '2023-11-20': {'1. open': '189.8900',
  '2. high': '191.9050',
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 '2023-11-17': {'1. open': '190.2500',
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 '2023-11-16': {'1. open': '189.5700',
  '2. high': '190.9600',
  '3. low': '188.6500',
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 '2023-11-15': {'1. open': '187.8450',
  '2. high': '189.5000',
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 '2023-11-14': {'1. open': '187.7000',
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 '2023-11-13': {'1. open': '185.8200',
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 '2023-11-10': {'1. open': '183.9700',
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 '2023-11-09': {'1. open': '182.9600',
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 '2023-11-08': {'1. open': '182.3500',
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 '2023-11-07': {'1. open': '179.1800',
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 '2023-11-06': {'1. open': '176.3800',
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 '2023-11-03': {'1. open': '174.2400',
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 '2023-11-02': {'1. open': '175.5200',
  '2. high': '177.7800',
  '3. low': '175.4600',
  '4. close': '177.5700',
  '5. volume': '77334752'},
 '2023-11-01': {'1. open': '171.0000',
  '2. high': '174.2300',
  '3. low': '170.1200',
  '4. close': '173.9700',
  '5. volume': '56934906'},
 '2023-10-31': {'1. open': '169.3500',
  '2. high': '170.9000',
  '3. low': '167.9000',
  '4. close': '170.7700',
  '5. volume': '44846017'},
 '2023-10-30': {'1. open': '169.0200',
  '2. high': '171.1700',
  '3. low': '168.8700',
  '4. close': '170.2900',
  '5. volume': '51130955'},
 '2023-10-27': {'1. open': '166.9100',
  '2. high': '168.9600',
  '3. low': '166.8300',
  '4. close': '168.2200',
  '5. volume': '58499129'},
 '2023-10-26': {'1. open': '170.3700',
  '2. high': '171.3775',
  '3. low': '165.6700',
  '4. close': '166.8900',
  '5. volume': '70625258'},
 '2023-10-25': {'1. open': '171.8800',
  '2. high': '173.0600',
  '3. low': '170.6500',
  '4. close': '171.1000',
  '5. volume': '57156962'},
 '2023-10-24': {'1. open': '173.0500',
  '2. high': '173.6700',
  '3. low': '171.4500',
  '4. close': '173.4400',
  '5. volume': '43816644'},
 '2023-10-23': {'1. open': '170.9100',
  '2. high': '174.0100',
  '3. low': '169.9300',
  '4. close': '173.0000',
  '5. volume': '55980109'},
 '2023-10-20': {'1. open': '175.3100',
  '2. high': '175.4200',
  '3. low': '172.6400',
  '4. close': '172.8800',
  '5. volume': '64244028'},
 '2023-10-19': {'1. open': '176.0400',
  '2. high': '177.8400',
  '3. low': '175.1900',
  '4. close': '175.4600',
  '5. volume': '59302863'},
 '2023-10-18': {'1. open': '175.5800',
  '2. high': '177.5750',
  '3. low': '175.1100',
  '4. close': '175.8400',
  '5. volume': '54764375'},
 '2023-10-17': {'1. open': '176.6450',
  '2. high': '178.4200',
  '3. low': '174.8000',
  '4. close': '177.1500',
  '5. volume': '57549350'},
 '2023-10-16': {'1. open': '176.7500',
  '2. high': '179.0750',
  '3. low': '176.5100',
  '4. close': '178.7200',
  '5. volume': '52516984'},
 '2023-10-13': {'1. open': '181.4200',
  '2. high': '181.9300',
  '3. low': '178.1400',
  '4. close': '178.8500',
  '5. volume': '51456082'},
 '2023-10-12': {'1. open': '180.0700',
  '2. high': '182.3400',
  '3. low': '179.0400',
  '4. close': '180.7100',
  '5. volume': '56743119'},
 '2023-10-11': {'1. open': '178.2000',
  '2. high': '179.8500',
  '3. low': '177.6000',
  '4. close': '179.8000',
  '5. volume': '47551098'},
 '2023-10-10': {'1. open': '178.1000',
  '2. high': '179.7200',
  '3. low': '177.9500',
  '4. close': '178.3900',
  '5. volume': '43698019'},
 '2023-10-09': {'1. open': '176.8100',
  '2. high': '179.0500',
  '3. low': '175.8000',
  '4. close': '178.9900',
  '5. volume': '42390772'},
 '2023-10-06': {'1. open': '173.8000',
  '2. high': '177.9900',
  '3. low': '173.1800',
  '4. close': '177.4900',
  '5. volume': '57266675'},
 '2023-10-05': {'1. open': '173.7900',
  '2. high': '175.4500',
  '3. low': '172.6800',
  '4. close': '174.9100',
  '5. volume': '48527918'},
 '2023-10-04': {'1. open': '171.0900',
  '2. high': '174.2100',
  '3. low': '170.9700',
  '4. close': '173.6600',
  '5. volume': '53020286'},
 '2023-10-03': {'1. open': '172.2550',
  '2. high': '173.6300',
  '3. low': '170.8200',
  '4. close': '172.4000',
  '5. volume': '49594613'},
 '2023-10-02': {'1. open': '171.2200',
  '2. high': '174.3000',
  '3. low': '170.9300',
  '4. close': '173.7500',
  '5. volume': '52164535'},
 '2023-09-29': {'1. open': '172.0200',
  '2. high': '173.0700',
  '3. low': '170.3410',
  '4. close': '171.2100',
  '5. volume': '51861083'},
 '2023-09-28': {'1. open': '169.3400',
  '2. high': '172.0300',
  '3. low': '167.6200',
  '4. close': '170.6900',
  '5. volume': '56294419'},
 '2023-09-27': {'1. open': '172.6200',
  '2. high': '173.0400',
  '3. low': '169.0500',
  '4. close': '170.4300',
  '5. volume': '66921808'},
 '2023-09-26': {'1. open': '174.8200',
  '2. high': '175.2000',
  '3. low': '171.6600',
  '4. close': '171.9600',
  '5. volume': '64588945'},
 '2023-09-25': {'1. open': '174.2000',
  '2. high': '176.9700',
  '3. low': '174.1500',
  '4. close': '176.0800',
  '5. volume': '46172740'},
 '2023-09-22': {'1. open': '174.6700',
  '2. high': '177.0790',
  '3. low': '174.0500',
  '4. close': '174.7900',
  '5. volume': '56725385'},
 '2023-09-21': {'1. open': '174.5500',
  '2. high': '176.3000',
  '3. low': '173.8600',
  '4. close': '173.9300',
  '5. volume': '63149116'},
 '2023-09-20': {'1. open': '179.2600',
  '2. high': '179.6950',
  '3. low': '175.4000',
  '4. close': '175.4900',
  '5. volume': '58436181'},
 '2023-09-19': {'1. open': '177.5200',
  '2. high': '179.6300',
  '3. low': '177.1300',
  '4. close': '179.0700',
  '5. volume': '51826941'},
 '2023-09-18': {'1. open': '176.4800',
  '2. high': '179.3800',
  '3. low': '176.1700',
  '4. close': '177.9700',
  '5. volume': '67257573'},
 '2023-09-15': {'1. open': '176.4800',
  '2. high': '176.4950',
  '3. low': '173.8200',
  '4. close': '175.0100',
  '5. volume': '109259461'},
 '2023-09-14': {'1. open': '174.0000',
  '2. high': '176.1000',
  '3. low': '173.5800',
  '4. close': '175.7400',
  '5. volume': '60895757'},
 '2023-09-13': {'1. open': '176.5100',
  '2. high': '177.3000',
  '3. low': '173.9800',
  '4. close': '174.2100',
  '5. volume': '84267928'},
 '2023-09-12': {'1. open': '179.4900',
  '2. high': '180.1300',
  '3. low': '174.8200',
  '4. close': '176.3000',
  '5. volume': '90370192'},
 '2023-09-11': {'1. open': '180.0700',
  '2. high': '180.3000',
  '3. low': '177.3400',
  '4. close': '179.3600',
  '5. volume': '58953052'},
 '2023-09-08': {'1. open': '178.3500',
  '2. high': '180.2390',
  '3. low': '177.7900',
  '4. close': '178.1800',
  '5. volume': '65602066'},
 '2023-09-07': {'1. open': '175.1800',
  '2. high': '178.2100',
  '3. low': '173.5400',
  '4. close': '177.5600',
  '5. volume': '112488803'},
 '2023-09-06': {'1. open': '188.4000',
  '2. high': '188.8500',
  '3. low': '181.4700',
  '4. close': '182.9100',
  '5. volume': '81755816'},
 '2023-09-05': {'1. open': '188.2800',
  '2. high': '189.9800',
  '3. low': '187.6100',
  '4. close': '189.7000',
  '5. volume': '45280027'},
 '2023-09-01': {'1. open': '189.4850',
  '2. high': '189.9200',
  '3. low': '188.2800',
  '4. close': '189.4600',
  '5. volume': '45766503'},
 '2023-08-31': {'1. open': '187.8400',
  '2. high': '189.1200',
  '3. low': '187.4800',
  '4. close': '187.8700',
  '5. volume': '60794467'},
 '2023-08-30': {'1. open': '184.9400',
  '2. high': '187.8500',
  '3. low': '184.7400',
  '4. close': '187.6500',
  '5. volume': '60813888'},
 '2023-08-29': {'1. open': '179.6950',
  '2. high': '184.9000',
  '3. low': '179.5000',
  '4. close': '184.1200',
  '5. volume': '53003948'},
 '2023-08-28': {'1. open': '180.0900',
  '2. high': '180.5900',
  '3. low': '178.5450',
  '4. close': '180.1900',
  '5. volume': '43820697'},
 '2023-08-25': {'1. open': '177.3800',
  '2. high': '179.1500',
  '3. low': '175.8200',
  '4. close': '178.6100',
  '5. volume': '51449594'},
 '2023-08-24': {'1. open': '180.6740',
  '2. high': '181.1040',
  '3. low': '176.0100',
  '4. close': '176.3800',
  '5. volume': '54945798'},
 '2023-08-23': {'1. open': '178.5200',
  '2. high': '181.5500',
  '3. low': '178.3250',
  '4. close': '181.1200',
  '5. volume': '52722752'},
 '2023-08-22': {'1. open': '177.0600',
  '2. high': '177.6800',
  '3. low': '176.2500',
  '4. close': '177.2300',
  '5. volume': '42084245'},
 '2023-08-21': {'1. open': '175.0700',
  '2. high': '176.1300',
  '3. low': '173.7350',
  '4. close': '175.8400',
  '5. volume': '46311879'},
 '2023-08-18': {'1. open': '172.3000',
  '2. high': '175.1000',
  '3. low': '171.9600',
  '4. close': '174.4900',
  '5. volume': '61172150'},
 '2023-08-17': {'1. open': '177.1400',
  '2. high': '177.5054',
  '3. low': '173.4800',
  '4. close': '174.0000',
  '5. volume': '66062882'},
 '2023-08-16': {'1. open': '177.1300',
  '2. high': '178.5400',
  '3. low': '176.5000',
  '4. close': '176.5700',
  '5. volume': '46964857'},
 '2023-08-15': {'1. open': '178.8800',
  '2. high': '179.4800',
  '3. low': '177.0500',
  '4. close': '177.4500',
  '5. volume': '43622593'},
 '2023-08-14': {'1. open': '177.9700',
  '2. high': '179.6900',
  '3. low': '177.3050',
  '4. close': '179.4600',
  '5. volume': '43675627'},
 '2023-08-11': {'1. open': '177.3200',
  '2. high': '178.6200',
  '3. low': '176.5500',
  '4. close': '177.7900',
  '5. volume': '52036672'},
 '2023-08-10': {'1. open': '179.4800',
  '2. high': '180.7500',
  '3. low': '177.6000',
  '4. close': '177.9700',
  '5. volume': '54686851'},
 '2023-08-09': {'1. open': '180.8700',
  '2. high': '180.9300',
  '3. low': '177.0100',
  '4. close': '178.1900',
  '5. volume': '60378492'},
 '2023-08-08': {'1. open': '179.6900',
  '2. high': '180.2700',
  '3. low': '177.5800',
  '4. close': '179.8000',
  '5. volume': '67823003'},
 '2023-08-07': {'1. open': '182.1300',
  '2. high': '183.1300',
  '3. low': '177.3500',
  '4. close': '178.8500',
  '5. volume': '97576069'},
 '2023-08-04': {'1. open': '185.5200',
  '2. high': '187.3800',
  '3. low': '181.9200',
  '4. close': '181.9900',
  '5. volume': '115956841'},
 '2023-08-03': {'1. open': '191.5700',
  '2. high': '192.3700',
  '3. low': '190.6900',
  '4. close': '191.1700',
  '5. volume': '62243282'}}
In [9]:
###if we want data of stocks of today so ....
data['Time Series (Daily)']['2023-12-22']
Out[9]:
{'1. open': '195.1800',
 '2. high': '195.4100',
 '3. low': '192.9700',
 '4. close': '193.6000',
 '5. volume': '37149570'}
In [10]:
data['Time Series (Daily)']['2023-12-22']['4. close']
Out[10]:
'193.6000'
In [11]:
data['Time Series (Daily)']['2023-12-22'].items()
Out[11]:
dict_items([('1. open', '195.1800'), ('2. high', '195.4100'), ('3. low', '192.9700'), ('4. close', '193.6000'), ('5. volume', '37149570')])
In [12]:
date = '2023-12-22'
type(date)
Out[12]:
str
In [13]:
data['Time Series (Daily)']['2023-12-22'].keys()
Out[13]:
dict_keys(['1. open', '2. high', '3. low', '4. close', '5. volume'])
In [14]:
data['Time Series (Daily)']['2023-12-22'].values()
Out[14]:
dict_values(['195.1800', '195.4100', '192.9700', '193.6000', '37149570'])
In [15]:
date = '2023-12-22'
type(date)
Out[15]:
str
In [16]:
import pandas as pd
dt = pd.to_datetime(date)
dt
Out[16]:
Timestamp('2023-12-22 00:00:00')
In [17]:
type(dt)
Out[17]:
pandas._libs.tslibs.timestamps.Timestamp
In [18]:
date = []
o = []
h = []
l = []
c = []
Vol = []
for key,value in data['Time Series (Daily)'].items():
    d = pd.to_datetime(key)
    date .append(d)
    o.append(float(value['1. open']))
    h.append(float(value['2. high']))
    l.append(float(value['3. low']))
    c.append(float(value['4. close']))
    Vol.append(int(value['5. volume']))
In [19]:
date
Out[19]:
[Timestamp('2023-12-22 00:00:00'),
 Timestamp('2023-12-21 00:00:00'),
 Timestamp('2023-12-20 00:00:00'),
 Timestamp('2023-12-19 00:00:00'),
 Timestamp('2023-12-18 00:00:00'),
 Timestamp('2023-12-15 00:00:00'),
 Timestamp('2023-12-14 00:00:00'),
 Timestamp('2023-12-13 00:00:00'),
 Timestamp('2023-12-12 00:00:00'),
 Timestamp('2023-12-11 00:00:00'),
 Timestamp('2023-12-08 00:00:00'),
 Timestamp('2023-12-07 00:00:00'),
 Timestamp('2023-12-06 00:00:00'),
 Timestamp('2023-12-05 00:00:00'),
 Timestamp('2023-12-04 00:00:00'),
 Timestamp('2023-12-01 00:00:00'),
 Timestamp('2023-11-30 00:00:00'),
 Timestamp('2023-11-29 00:00:00'),
 Timestamp('2023-11-28 00:00:00'),
 Timestamp('2023-11-27 00:00:00'),
 Timestamp('2023-11-24 00:00:00'),
 Timestamp('2023-11-22 00:00:00'),
 Timestamp('2023-11-21 00:00:00'),
 Timestamp('2023-11-20 00:00:00'),
 Timestamp('2023-11-17 00:00:00'),
 Timestamp('2023-11-16 00:00:00'),
 Timestamp('2023-11-15 00:00:00'),
 Timestamp('2023-11-14 00:00:00'),
 Timestamp('2023-11-13 00:00:00'),
 Timestamp('2023-11-10 00:00:00'),
 Timestamp('2023-11-09 00:00:00'),
 Timestamp('2023-11-08 00:00:00'),
 Timestamp('2023-11-07 00:00:00'),
 Timestamp('2023-11-06 00:00:00'),
 Timestamp('2023-11-03 00:00:00'),
 Timestamp('2023-11-02 00:00:00'),
 Timestamp('2023-11-01 00:00:00'),
 Timestamp('2023-10-31 00:00:00'),
 Timestamp('2023-10-30 00:00:00'),
 Timestamp('2023-10-27 00:00:00'),
 Timestamp('2023-10-26 00:00:00'),
 Timestamp('2023-10-25 00:00:00'),
 Timestamp('2023-10-24 00:00:00'),
 Timestamp('2023-10-23 00:00:00'),
 Timestamp('2023-10-20 00:00:00'),
 Timestamp('2023-10-19 00:00:00'),
 Timestamp('2023-10-18 00:00:00'),
 Timestamp('2023-10-17 00:00:00'),
 Timestamp('2023-10-16 00:00:00'),
 Timestamp('2023-10-13 00:00:00'),
 Timestamp('2023-10-12 00:00:00'),
 Timestamp('2023-10-11 00:00:00'),
 Timestamp('2023-10-10 00:00:00'),
 Timestamp('2023-10-09 00:00:00'),
 Timestamp('2023-10-06 00:00:00'),
 Timestamp('2023-10-05 00:00:00'),
 Timestamp('2023-10-04 00:00:00'),
 Timestamp('2023-10-03 00:00:00'),
 Timestamp('2023-10-02 00:00:00'),
 Timestamp('2023-09-29 00:00:00'),
 Timestamp('2023-09-28 00:00:00'),
 Timestamp('2023-09-27 00:00:00'),
 Timestamp('2023-09-26 00:00:00'),
 Timestamp('2023-09-25 00:00:00'),
 Timestamp('2023-09-22 00:00:00'),
 Timestamp('2023-09-21 00:00:00'),
 Timestamp('2023-09-20 00:00:00'),
 Timestamp('2023-09-19 00:00:00'),
 Timestamp('2023-09-18 00:00:00'),
 Timestamp('2023-09-15 00:00:00'),
 Timestamp('2023-09-14 00:00:00'),
 Timestamp('2023-09-13 00:00:00'),
 Timestamp('2023-09-12 00:00:00'),
 Timestamp('2023-09-11 00:00:00'),
 Timestamp('2023-09-08 00:00:00'),
 Timestamp('2023-09-07 00:00:00'),
 Timestamp('2023-09-06 00:00:00'),
 Timestamp('2023-09-05 00:00:00'),
 Timestamp('2023-09-01 00:00:00'),
 Timestamp('2023-08-31 00:00:00'),
 Timestamp('2023-08-30 00:00:00'),
 Timestamp('2023-08-29 00:00:00'),
 Timestamp('2023-08-28 00:00:00'),
 Timestamp('2023-08-25 00:00:00'),
 Timestamp('2023-08-24 00:00:00'),
 Timestamp('2023-08-23 00:00:00'),
 Timestamp('2023-08-22 00:00:00'),
 Timestamp('2023-08-21 00:00:00'),
 Timestamp('2023-08-18 00:00:00'),
 Timestamp('2023-08-17 00:00:00'),
 Timestamp('2023-08-16 00:00:00'),
 Timestamp('2023-08-15 00:00:00'),
 Timestamp('2023-08-14 00:00:00'),
 Timestamp('2023-08-11 00:00:00'),
 Timestamp('2023-08-10 00:00:00'),
 Timestamp('2023-08-09 00:00:00'),
 Timestamp('2023-08-08 00:00:00'),
 Timestamp('2023-08-07 00:00:00'),
 Timestamp('2023-08-04 00:00:00'),
 Timestamp('2023-08-03 00:00:00')]
In [20]:
date[0:5]
Out[20]:
[Timestamp('2023-12-22 00:00:00'),
 Timestamp('2023-12-21 00:00:00'),
 Timestamp('2023-12-20 00:00:00'),
 Timestamp('2023-12-19 00:00:00'),
 Timestamp('2023-12-18 00:00:00')]
In [21]:
o[0:5]
Out[21]:
[195.18, 196.1, 196.9, 196.16, 196.09]
In [22]:
h[0:5]
Out[22]:
[195.41, 197.08, 197.68, 196.95, 196.63]
In [23]:
l[0:5]
Out[23]:
[192.97, 193.5, 194.83, 195.89, 194.39]
In [24]:
c[0:5]
Out[24]:
[193.6, 194.68, 194.83, 196.94, 195.89]
In [25]:
Vol[0:5]
Out[25]:
[37149570, 46482549, 52242815, 40233138, 55751861]

Create a dataframe¶

In [26]:
dct = {'Open' : o,
       'High' : h,
       'Low' : l,
       'Close' : c,
       'Volume' : Vol}
In [27]:
df  = pd.DataFrame(dct , index = date)
df
Out[27]:
Open High Low Close Volume
2023-12-22 195.18 195.41 192.97 193.60 37149570
2023-12-21 196.10 197.08 193.50 194.68 46482549
2023-12-20 196.90 197.68 194.83 194.83 52242815
2023-12-19 196.16 196.95 195.89 196.94 40233138
2023-12-18 196.09 196.63 194.39 195.89 55751861
... ... ... ... ... ...
2023-08-09 180.87 180.93 177.01 178.19 60378492
2023-08-08 179.69 180.27 177.58 179.80 67823003
2023-08-07 182.13 183.13 177.35 178.85 97576069
2023-08-04 185.52 187.38 181.92 181.99 115956841
2023-08-03 191.57 192.37 190.69 191.17 62243282

100 rows × 5 columns

In [28]:
df = df.sort_index()
df
Out[28]:
Open High Low Close Volume
2023-08-03 191.57 192.37 190.69 191.17 62243282
2023-08-04 185.52 187.38 181.92 181.99 115956841
2023-08-07 182.13 183.13 177.35 178.85 97576069
2023-08-08 179.69 180.27 177.58 179.80 67823003
2023-08-09 180.87 180.93 177.01 178.19 60378492
... ... ... ... ... ...
2023-12-18 196.09 196.63 194.39 195.89 55751861
2023-12-19 196.16 196.95 195.89 196.94 40233138
2023-12-20 196.90 197.68 194.83 194.83 52242815
2023-12-21 196.10 197.08 193.50 194.68 46482549
2023-12-22 195.18 195.41 192.97 193.60 37149570

100 rows × 5 columns

Install Plotly and nbformat package¶

In [29]:
%pip install plotly nbformat

Requirement already satisfied: plotly in c:\users\dell\appdata\local\anaconda3\lib\site-packages (5.9.0)
Requirement already satisfied: nbformat in c:\users\dell\appdata\local\anaconda3\lib\site-packages (5.7.0)
Requirement already satisfied: tenacity>=6.2.0 in c:\users\dell\appdata\local\anaconda3\lib\site-packages (from plotly) (8.2.2)
Requirement already satisfied: fastjsonschema in c:\users\dell\appdata\local\anaconda3\lib\site-packages (from nbformat) (2.16.2)
Requirement already satisfied: jsonschema>=2.6 in c:\users\dell\appdata\local\anaconda3\lib\site-packages (from nbformat) (4.17.3)
Requirement already satisfied: jupyter-core in c:\users\dell\appdata\local\anaconda3\lib\site-packages (from nbformat) (5.3.0)
Requirement already satisfied: traitlets>=5.1 in c:\users\dell\appdata\local\anaconda3\lib\site-packages (from nbformat) (5.7.1)
Requirement already satisfied: attrs>=17.4.0 in c:\users\dell\appdata\local\anaconda3\lib\site-packages (from jsonschema>=2.6->nbformat) (22.1.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in c:\users\dell\appdata\local\anaconda3\lib\site-packages (from jsonschema>=2.6->nbformat) (0.18.0)
Requirement already satisfied: platformdirs>=2.5 in c:\users\dell\appdata\local\anaconda3\lib\site-packages (from jupyter-core->nbformat) (2.5.2)
Requirement already satisfied: pywin32>=300 in c:\users\dell\appdata\local\anaconda3\lib\site-packages (from jupyter-core->nbformat) (305.1)
Note: you may need to restart the kernel to use updated packages.

Restart and run all cells¶

In [30]:
df.index
Out[30]:
DatetimeIndex(['2023-08-03', '2023-08-04', '2023-08-07', '2023-08-08',
               '2023-08-09', '2023-08-10', '2023-08-11', '2023-08-14',
               '2023-08-15', '2023-08-16', '2023-08-17', '2023-08-18',
               '2023-08-21', '2023-08-22', '2023-08-23', '2023-08-24',
               '2023-08-25', '2023-08-28', '2023-08-29', '2023-08-30',
               '2023-08-31', '2023-09-01', '2023-09-05', '2023-09-06',
               '2023-09-07', '2023-09-08', '2023-09-11', '2023-09-12',
               '2023-09-13', '2023-09-14', '2023-09-15', '2023-09-18',
               '2023-09-19', '2023-09-20', '2023-09-21', '2023-09-22',
               '2023-09-25', '2023-09-26', '2023-09-27', '2023-09-28',
               '2023-09-29', '2023-10-02', '2023-10-03', '2023-10-04',
               '2023-10-05', '2023-10-06', '2023-10-09', '2023-10-10',
               '2023-10-11', '2023-10-12', '2023-10-13', '2023-10-16',
               '2023-10-17', '2023-10-18', '2023-10-19', '2023-10-20',
               '2023-10-23', '2023-10-24', '2023-10-25', '2023-10-26',
               '2023-10-27', '2023-10-30', '2023-10-31', '2023-11-01',
               '2023-11-02', '2023-11-03', '2023-11-06', '2023-11-07',
               '2023-11-08', '2023-11-09', '2023-11-10', '2023-11-13',
               '2023-11-14', '2023-11-15', '2023-11-16', '2023-11-17',
               '2023-11-20', '2023-11-21', '2023-11-22', '2023-11-24',
               '2023-11-27', '2023-11-28', '2023-11-29', '2023-11-30',
               '2023-12-01', '2023-12-04', '2023-12-05', '2023-12-06',
               '2023-12-07', '2023-12-08', '2023-12-11', '2023-12-12',
               '2023-12-13', '2023-12-14', '2023-12-15', '2023-12-18',
               '2023-12-19', '2023-12-20', '2023-12-21', '2023-12-22'],
              dtype='datetime64[ns]', freq=None)
In [31]:
import plotly.graph_objects as go
In [33]:
fig = go.Figure(data=[go.Candlestick(x=df.index,
                               open=df['Open'],
                               high=df['High'],
                               low=df['Low'],
                               close=df['Close'])])
fig.show()
In [34]:
import plotly.express as px
In [35]:
fig2 = px.line(df , x = df.index , y = df['Close'] , title = 'Closing price for AAPL' )
fig2.show()

Fetching The symbols for any company : Search Endpoint¶

In [36]:
import requests

url = "https://alpha-vantage.p.rapidapi.com/query"

querystring = {"keywords":"State Bank of India","function":"SYMBOL_SEARCH","datatype":"json"}

headers = {
    "X-RapidAPI-Key": "4671befe8emsh7013c7cb33388c1p12bea1jsna736eefbd6fc",
    "X-RapidAPI-Host": "alpha-vantage.p.rapidapi.com"
}

response = requests.get(url, headers=headers, params=querystring)

(response.json())
Out[36]:
{'bestMatches': [{'1. symbol': 'SBIN.BSE',
   '2. name': 'State Bank of India',
   '3. type': 'Equity',
   '4. region': 'India/Bombay',
   '5. marketOpen': '09:15',
   '6. marketClose': '15:30',
   '7. timezone': 'UTC+5.5',
   '8. currency': 'INR',
   '9. matchScore': '1.0000'},
  {'1. symbol': 'SBKFF',
   '2. name': 'State Bank of India',
   '3. type': 'Equity',
   '4. region': 'United States',
   '5. marketOpen': '09:30',
   '6. marketClose': '16:00',
   '7. timezone': 'UTC-04',
   '8. currency': 'USD',
   '9. matchScore': '1.0000'},
  {'1. symbol': 'SID.FRK',
   '2. name': 'State Bank of India',
   '3. type': 'Equity',
   '4. region': 'Frankfurt',
   '5. marketOpen': '08:00',
   '6. marketClose': '20:00',
   '7. timezone': 'UTC+02',
   '8. currency': 'EUR',
   '9. matchScore': '1.0000'},
  {'1. symbol': 'SBID.LON',
   '2. name': 'State Bank of India GDR',
   '3. type': 'Equity',
   '4. region': 'United Kingdom',
   '5. marketOpen': '08:00',
   '6. marketClose': '16:30',
   '7. timezone': 'UTC+01',
   '8. currency': 'USD',
   '9. matchScore': '0.9048'}]}

Advance Python Finishes here¶

In [ ]: